(373ag) Predictive Resilience and Equitable Risk Assessment in Supply Chains Via Consensus-Driven Inverse Neural Network on Interoperable Blockchains

The recent global disruptions in sectors like semiconductor manufacturing, large capacity batteries, critical minerals/materials and pharmaceuticals/active pharmaceutical ingredients industry have highlighted the critical importance of supply chain resilience and visibility [1]. These challenges, exacerbated by the COVID-19 pandemic, climate change, labor shocks, and geopolitical tensions, underscore the vulnerabilities of traditional supply chains and the pressing need for digitalization [2, 3]. Supply chain interruptions are causing economic difficulties, with firms worldwide losing an average of 184 million U.S. dollars each year as per 2021 surveys. In the United States, the financial burden is largest, with an estimated average yearly cost of 228 million U.S. dollars [4]. According to a McKinsey report, companies face an average potential loss of 45% of annual profits once per decade due to these disruptions [5]. This situation is exacerbated by the fact that 74% of supply chain managers still rely on manual processes, as reported by Interos, leading to low visibility and increased vulnerability to a range of risks including cybersecurity threats, weather events, power outages, and global health crises [6]. Digital technologies such as cloud computing, AI, and blockchain are pivotal in enhancing supply chain efficiency and resilience. AI improves demand forecasting and sourcing strategies, while blockchain offers a secure, transparent record of transactions, enabling comprehensive monitoring of both primary and secondary suppliers. This digitalization facilitates the early detection of vulnerabilities, supports shared stress testing, and ensures equitable risk sharing among participants. By adopting a holistic approach that leverages these technologies, we can build a robust, responsive supply chain ecosystem capable of withstanding the multifaceted challenges of the global market, particularly in interconnected, multi-sectoral supply chains where disruptions have cascading effects across industries.

In this work, I propose a novel approach utilizing Consensus-Driven Inverse Physics-Informed Neural Network (IPINN) mapping on interoperable blockchains (i-Block) to achieve predictive resilience and equitable risk assessment in supply chains. The key innovation lies in leveraging IPINNs to map the intricate architecture of supply chains, replicating the relationships between nodes while considering factors such as demand satisfaction (represented by weights) and supply availability (represented by biases). By embedding this mapping within a consensus-driven framework and incorporating game theory-based optimization, the proposed approach aims to identify optimal configurations for supply chain networks. The initial phase of the research focuses on determining the optimal parameters, including weights, biases, and activation functions, to identify influential nodes and assess their impact on network resilience. Subsequently, stress testing using the IPINN mapping will enable the identification of vulnerable nodes and prompt actions for disruption recovery. Resiliency involves the capability to adapt to changing conditions and to recover from disruptions through collaborative efforts. The overall objective is to minimize the total impact of disruptions on the supply chain while maximizing the collaborative resiliency score (CRS) across all nodes in the network.

Furthermore, the proposed approach integrates blockchain technology to facilitate transparent, anonymous, and secure circulation of action plans among stakeholders. It aims to enhance the visibility of complex supply chain networks while ensuring data privacy and security. This is achieved by deploying cryptographic techniques like zero-knowledge proofs and secure multi-party computation, enabling transaction verification and data integrity without compromising sensitive information [7]. Secondly, i-Block emphasizes resilience by facilitating stress-testing environments where multiple firms can collaboratively assess and manage shared risks without endangering data sovereignty, utilizing consensus algorithms such as Proof of Stake (PoS) or Practical Byzantine Fault Tolerance (PBFT). Thirdly, the work leverages an IoT-enabled blockchain framework for real-time monitoring, where smart sensors and RFID tags collect and immutably record essential data points like temperature and location, allowing for the timely identification of vulnerabilities in demand, supply, technology, or workforce availability. Moreover, i-Block ensures economic sustainability for firms of varied sizes and competencies, enabling their participation in proactive resilience management through tokenization, smart contracts that automate business agreements and reduce transactional overheads, and by the strategic game theory applications. This ensures consensus-based decision-making and fair distribution of action plans, thereby mitigating the potential exploitation of uncertainties by dominant players. i-Block's innovative approach includes the application of Generalized Nash Equilibrium (GNE) and concepts like the Shapley value from cooperative game theory, offering a sophisticated model to analyze supply chain dynamics and ensure equitable risk sharing among participants. The model’s parameters, decision variables, and outcomes will be embedded in the Inter Planetary File System (IPFS), ensuring decentralized storage and easy access for all supply chain participants. Smart contracts will automate the execution of the consensus mechanism, update strategies based on the model's outcomes, and enforce agreed-upon resiliency strategies. A key feature of i-Block is its focus on interoperability, achieved through API gateways and cross-chain protocols such as Cosmos or Polkadot, enabling seamless data exchange across different blockchain platforms. This interoperability is crucial for constructing a unified view of the supply chain, identifying hidden dependencies, and mitigating single points of failure. This proposed i-Block approach not only ensures operational continuity during disruptions but also offers a competitive edge by enabling supply chain stakeholders to swiftly adapt to changing dynamics, thereby redefining industry standards for supply chain management in the digital age.

References

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